Sign Language Recognition by Means of Common Spatial Patterns

Currently, and despite the efforts that have been made, people with hearing impairments often have difficulties to use applications that have been designed for people who can hear, or simply to communicate with their environment. In this work, we present an Argentinian Sign Language (LSA) recognition system which distinguishes between different signs using hand landmarks extracted from the videos of the dataset. The Common Spatial Patterns (CSP) algorithm is used to extract features, and the classification is performed with multiple classifiers. Different experiments have been made from which promising results have been obtained.